Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. We present the SODA Synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multi-level representations to progressively lower and optimize the input code. Our approach does not require the application developer to write register-transfer level code, and it is able to reach up to 364 GFLOPS/W efficiency (32-bit precision) on typical convolutional neural network operators

Real-time plasma state monitoring and supervisory control on TCV

In ITER and DEMO, various control objectives related to plasma control must be simultaneously achieved by the plasma control system (PCS), in both normal operation as well as off-normal conditions. The PCS must act on off-normal events and deviations from the target scenario, since certain sequences (chains) of events can precede disruptions. It is important that these decisions are made while maintaining a coherent prioritization between the real-time control tasks to ensure high-performance operation. In this paper, a generic architecture for task-based integrated plasma control is proposed. The architecture is characterized by the separation of state estimation, event detection, decisions and task execution among different algorithms, with standardized signal interfaces. Central to the architecture are a plasma state monitor and supervisory controller. In the plasma state monitor, discrete events in the continuous-valued plasma state are modeled using finite state machines. This provides a high-level representation of the plasma state. The supervisory controller coordinates the execution of multiple plasma control tasks by assigning task priorities, based on the finite states of the plasma and the pulse schedule. These algorithms were implemented on the TCV digital control system and integrated with actuator resource management and existing state estimation algorithms and controllers. The plasma state monitor on TCV can track a multitude of plasma events, related to plasma current, rotating and locked neoclassical tearing modes, and position displacements. In TCV experiments on simultaneous control of plasma pressure, safety factor profile and NTMs using electron cyclotron heating (ECH) and current drive (ECCD), the supervisory controller assigns priorities to the relevant control tasks. The tasks are then executed by feedback controllers and actuator allocation management. This work forms a significant step forward in the ongoing integration of control capabilities in experiments on TCV, in support of tokamak reactor operation

Barley starch

This thesis examined barley amylopectin structure and looked for correlations between the structure and physical properties of starch. The structure of amylopectin and gelatinisation and retrogradation of starch were studied in 10 different barley cultivars/breeding lines with differing genetic background. Amylopectin is built up of thousands of chains of glucose monomers, organised into clusters. The detailed fine structure of amylopectin was studied by isolating clusters of amylopectin and their building blocks, which are the tightly branched units building up the clusters. Barley cultivars/breeding lines possessing the amo1 mutation had fewer long chains of DP≥38 in amylopectin and more large building blocks. The structure of building blocks was rather conserved between the different barley cultivars/breeding lines studied and was categorized into different size groups. These different building blocks were shown to be randomly distributed in the amylopectin molecule. The C-chains in amylopectin can be of any length and are a category of chains different from the B-chains. The backbone in amylopectin consists of a special type of B-chains which, when cleaved by α-amylase, become chains of a similar type to C-chains. Gelatinisation and retrogradation (recrystallisation of gelatinised starch) of barley starch was studied by differential scanning calorimetry. The amo1 mutation resulted in a broader gelatinisation temperature range and a higher enthalpy of retrogradation. Other structural features were also found to influence the physical properties of starch. Small clusters and denser structure of the building blocks resulted in higher gelatinisation temperature. Fast retrogradation was observed in barley which had amylopectin with shorter chains and many large building blocks consisting of many chains. Amylopectin structure was also studied in developing barley kernels. Three barley cultivars/breeding lines were grown in a phytotron and kernels were harvested at 9, 12 and 24 days after flowering. The results showed that amylopectin synthesized at later stages of development had a more tightly branched structure. Expression of the enzymes involved in starch biosynthesis is also known to change during endosperm development

Comparison of runaway electron generation parameters in small, medium-sized and large tokamaks - A survey of experiments in COMPASS, TCV, ASDEX-Upgrade and JET

This paper presents a survey of the experiments on runaway electrons (RE) carried out recently in frames of EUROFusion Consortium in different tokamaks: COMPASS, ASDEX-Upgrade, TCV and JET. Massive gas injection (MGI) has been used in different scenarios for RE generation in small and medium-sized tokamaks to elaborate the most efficient and reliable ones for future RE experiments. New data on RE generated at disruptions in COMPASS and ASDEX-Upgrade was collected and added to the JET database. Different accessible parameters of disruptions, such as current quench rate, conversion rate of plasma current into runaways, etc have been analysed for each tokamak and compared to JET data. It was shown, that tokamaks with larger geometrical sizes provide the wider limits for spatial and temporal variation of plasma parameters during disruptions, thus extending the parameter space for RE generation. The second part of experiments was dedicated to study of RE generation in stationary discharges in COMPASS, TCV and JET. Injection of Ne/Ar have been used to mock-up the JET MGI runaway suppression experiments. Secondary RE avalanching was identified and quantified for the first time in the TCV tokamak in RE generating discharges after massive Ne injection. Simulations of the primary RE generation and secondary avalanching dynamics in stationary discharges has demonstrated that RE current fraction created via avalanching could achieve up to 70-75% of the total plasma current in TCV. Relaxations which are reminiscent the phenomena associated to the kinetic instability driven by RE have been detected in RE discharges in TCV. Macroscopic parameters of RE dominating discharges in TCV before and after onset of the instability fit well to the empirical instability criterion, which was established in the early tokamaks and examined by results of recent numerical simulations

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

1488siThe RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of T e, T i and n e have been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks.reservedmixedRedondo J.; Meyer H.; Eich Th.; Beurskens M.; Coda S.; Hakola A.; Martin P.; Adamek J.; Agostini M.; Aguiam D.; Ahn J.; Aho-Mantila L.; Akers R.; Albanese R.; Aledda R.; Alessi E.; Allan S.; Alves D.; Ambrosino R.; Amicucci L.; Anand H.; Anastassiou G.; Andrebe Y.; Angioni C.; Apruzzese G.; Ariola M.; Arnichand H.; Arter W.; Baciero A.; Barnes M.; Barrera L.; Behn R.; Bencze A.; Bernardo J.; Bernert M.; Bettini P.; Bilkova P.; Bin W.; Birkenmeier G.; Bizarro J.P.S.; Blanchard P.; Blanken T.; Bluteau M.; Bobkov V.; Bogar O.; Bohm P.; Bolzonella T.; Boncagni L.; Botrugno A.; Bottereau C.; Bouquey F.; Bourdelle C.; Bremond S.; Brezinsek S.; Brida D.; Brochard F.; Buchanan J.; Bufferand H.; Buratti P.; Cahyna P.; Calabro G.; Camenen Y.; Caniello R.; Cannas B.; Canton A.; 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Moreira L.; Moreno R.; Moro F.; Morris A.W.; Morris J.; Moser L.; Mosher S.; Murari A.; Muraro A.; Murphy S.; Asakura N.N.; Na Y.S.; Naish R.; Nakano T.; Nave M.F.F.; Nedzelski I.; Nemtsev G.; Neto A.; Neverov V.S.; Newman M.; Nicholls K.J.; Nicolas T.; Nielsen P.; Nilsson E.; Nishijima D.; Noble C.; Nodwell D.; Nordlund K.; Nordman H.; Nunes I.; Odupitan T.; Ogawa M.T.; O'Gorman T.; Okabayashi M.; Olney R.; Omolayo O.; O'Mullane M.; Ongena J.; Orsitto F.; Orszagh J.; Oswuigwe B.I.; Otin R.; Owen A.; Pace N.; Pacella D.; Packer L.W.; Page A.; Pajuste E.; Palazzo S.; Panja S.; Papp P.; Park M.; Diaz F.P.; Parsons M.; Pasqualotto R.; Patel A.; Pathak S.; Paton D.; Patten H.; Pawelec E.; Soldan C.P.; Peackoc A.; Pearson I.J.; Peluso E.; Penot C.; Pereira R.; Puglia P.P.P.; von Thun C.P.; Peruzzo S.; Peschanyi S.; Petravich G.; Petre A.; Petrella N.; Peysson Y.; Pfefferle D.; Philipps V.; Pillon M.; Pintsuk G.; dos Reis A.P.; Piron L.; Pizzo F.; Pomaro N.; Pompilian O.G.; Pool P.J.; Popovichev S.; Porfiri M.T.; Porosnicu C.; Porton M.; Possnert G.; Powell T.; Pozzi J.; Prajapati V.; Prakash R.; Prestopino G.; Price D.; Price M.; Price R.; Prior P.; Proudfoot R.; Puglia P.; Pulley D.; Purahoo K.; Putterich Th.; Rachlew E.; Ragona R.; Rainford M.S.J.; Rakha A.; Ranjan S.; Rapson C.J.; Rathod K.; Ratta G.; Rayner C.; Rebai M.; Reece D.; Reed A.; Regan B.; Regana J.; Reid N.; Reinhart M.; Rendell D.; Cortes S.D.A.R.; Reynolds S.; Riccardo V.; Richardson N.; Riddle K.; Rigamonti D.; Rimini F.G.; Risner J.; Riva M.; Roach C.; Robins R.J.; Robinson S.A.; Robinson T.; Robson D.W.; Roccella R.; Rodionov R.; Rodrigues P.; Rodriguez J.; Romanelli F.; Romanelli M.; Romanelli S.; Romazanov J.; Rowe S.; Rubel M.; Rubinacci G.; Rubino G.; Ruchko L.; Ruiz M.; Ruset C.; Rzadkiewicz J.; Safi E.; Sagar P.; Saibene G.; Salmon R.; Salzedas F.; Samm U.; Sandiford D.; Santa P.; Santala M.I.K.; Santos B.; Santucci A.; Sartori F.; Sartori R.; Schlummer T.; Schmid K.; Schmidt V.; Schmuck S.; Schopf K.; Schworer D.; Scott S.D.; Sergienko G.; Shaw A.; Shaw R.; Shepherd A.; Shevelev A.; Shumack A.; Sibbald M.; Silburn S.; Simmons P.A.; Simpson-Hutchinson J.; Sinha A.; Sipila S.K.; Sips A.C.C.; Siren P.; Sirinelli A.; Sjostrand H.; Skiba M.; Skilton R.; Slabkowska K.; Slade B.; Smith N.; Smith P.G.; Smith R.; Smith T.J.; Smithies M.; Snoj L.; Soare S.; Solano E.R.; Somers A.; Sonato P.; Sopplesa A.; Sousa J.; Spelzini T.; Spineanu F.; Stables G.; Stamatelatos I.; Stamp M.F.; Staniec P.; Stankunas G.; Stan-Sion C.; Stead M.J.; Stefanikova E.; Stephen A.V.; Stephen M.; Stevens A.; Stevens B.D.; Strachan J.; Strauss H.R.; Strom P.; Stubbs G.; Studholme W.; Subba F.; Summers H.P.; Svensson J.; Swiderski L.; Szabolics T.; Szawlowski M.; Szepesi G.; Suzuki T.T.; Talbot A.R.; Talebzadeh S.; Taliercio C.; Tame C.; Tang W.; Taroni L.; Taylor D.; Taylor K.A.; Tegnered D.; Telesca G.; Teplova N.; Tholerus E.; Thomas J.; Thomas J.D.; Thomas P.; Thompson A.; Thompson C.-A.; Thompson V.K.; Thorne L.; Thrysoe A.S.; 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P. S.; Blanchard, P.; Blanken, T.; Bluteau, M.; Bobkov, V.; Bogar, O.; Bohm, P.; Bolzonella, T.; Boncagni, L.; Botrugno, A.; Bottereau, C.; Bouquey, F.; Bourdelle, C.; Bremond, S.; Brezinsek, S.; Brida, D.; Brochard, F.; Buchanan, J.; Bufferand, H.; Buratti, P.; Cahyna, P.; Calabro, G.; Camenen, Y.; Caniello, R.; Cannas, B.; Canton, A.; Cardinali, A.; Carnevale, D.; Carr, M.; Carralero, D.; Carvalho, P.; Casali, L.; Castaldo, C.; Castejon, F.; Castro, R.; Causa, F.; Cavazzana, R.; Cavedon, M.; Cecconello, M.; Ceccuzzi, S.; Cesario, R.; Challis, C. D.; Chapman, I. T.; Chapman, S. C.; Chernyshova, M.; Choi, D.; Cianfarani, C.; Ciraolo, G.; Citrin, J.; Clairet, F.; Classen, I.; Coelho, R.; Coenen, J. W.; Colas, L.; Conway, G.; Corre, Y.; Costea, S.; Crisanti, F.; Cruz, N.; Cseh, G.; Czarnecka, A.; D'Arcangelo, O.; de Angeli, M.; de Masi, G.; de Temmerman, G.; de Tommasi, G.; Decker, J.; Delogu, R. S.; Dendy, R. O.; Denner, P.; Di Troia, C.; Dimitrova, M.; D'Inca, R.; Doric, V.; Douai, D.; Drenik, A.; Dudson, B.; Dunai, D.; Dunne, M.; Duval, B. P.; Easy, L.; Elmore, S.; Erdos, B.; Esposito, B.; Fable, E.; Faitsch, M.; Fanni, A.; Fedorczak, N.; Felici, F.; Ferreira, J.; Fevrier, O.; Ficker, O.; Fietz, S.; Figini, L.; Figueiredo, A.; Fil, A.; Fishpool, G.; Fitzgerald, M.; Fontana, M.; Ford, O.; Frassinetti, L.; Fridstrom, R.; Frigione, D.; Fuchert, G.; Fuchs, C.; Palumbo, M. F.; Futatani, S.; Gabellieri, L.; Galazka, K.; Galdon-Quiroga, J.; Galeani, S.; Gallart, D.; Gallo, A.; Galperti, C.; Gao, Y.; Garavaglia, S.; Garcia, J.; Garcia-Carrasco, A.; Garcia-Lopez, J.; Garcia-Munoz, M.; Gardarein, J. -L.; Garzotti, L.; Gaspar, J.; Gauthier, E.; Geelen, P.; Geiger, B.; Ghendrih, P.; Ghezzi, F.; Giacomelli, L.; Giannone, L.; Giovannoz